US7175588B2 - Method and system for detecting ventricular collapse - Google Patents
Method and system for detecting ventricular collapse Download PDFInfo
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- US7175588B2 US7175588B2 US10/501,275 US50127504A US7175588B2 US 7175588 B2 US7175588 B2 US 7175588B2 US 50127504 A US50127504 A US 50127504A US 7175588 B2 US7175588 B2 US 7175588B2
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M60/00—Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance
- A61M60/40—Details relating to driving
- A61M60/403—Details relating to driving for non-positive displacement blood pumps
- A61M60/422—Details relating to driving for non-positive displacement blood pumps the force acting on the blood contacting member being electromagnetic, e.g. using canned motor pumps
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- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M60/00—Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance
- A61M60/10—Location thereof with respect to the patient's body
- A61M60/122—Implantable pumps or pumping devices, i.e. the blood being pumped inside the patient's body
- A61M60/165—Implantable pumps or pumping devices, i.e. the blood being pumped inside the patient's body implantable in, on, or around the heart
- A61M60/178—Implantable pumps or pumping devices, i.e. the blood being pumped inside the patient's body implantable in, on, or around the heart drawing blood from a ventricle and returning the blood to the arterial system via a cannula external to the ventricle, e.g. left or right ventricular assist devices
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- A61M60/00—Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance
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- A61M60/216—Non-positive displacement blood pumps including a rotating member acting on the blood, e.g. impeller
- A61M60/237—Non-positive displacement blood pumps including a rotating member acting on the blood, e.g. impeller the blood flow through the rotating member having mainly axial components, e.g. axial flow pumps
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- A61M60/00—Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance
- A61M60/50—Details relating to control
- A61M60/508—Electronic control means, e.g. for feedback regulation
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- A61M60/523—Regulation using real-time patient data using blood flow data, e.g. from blood flow transducers
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- A—HUMAN NECESSITIES
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- A61M60/00—Blood pumps; Devices for mechanical circulatory actuation; Balloon pumps for circulatory assistance
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- A—HUMAN NECESSITIES
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- A61M60/122—Implantable pumps or pumping devices, i.e. the blood being pumped inside the patient's body
- A61M60/126—Implantable pumps or pumping devices, i.e. the blood being pumped inside the patient's body implantable via, into, inside, in line, branching on, or around a blood vessel
- A61M60/148—Implantable pumps or pumping devices, i.e. the blood being pumped inside the patient's body implantable via, into, inside, in line, branching on, or around a blood vessel in line with a blood vessel using resection or like techniques, e.g. permanent endovascular heart assist devices
Definitions
- the invention relates generally to implanted or implantable blood pump systems, and more specifically, to a method and system for detecting the onset and/or presence of ventricular collapse associated with such pumps.
- implantable blood pump systems are employed in either of two circumstances. First an implantable blood pump may completely replace a human heart that is not functioning properly, or second, an implantable blood pump may boost blood circulation in patients whose heart is still functioning although pumping at an inadequate rate.
- U.S. Pat. No. 6,183,412 which is commonly assigned and incorporated herein by reference in its entirety, discloses a ventricle assist device (VAD) commercially referred to as the “DeBakey VAD®”.
- VAD ventricle assist device
- the VAD is a miniaturized continuous axial-flow pump designed to provide additional blood flow to patients who suffer from heart disease.
- the device is attached between the apex of the left ventricle and the aorta. Proper blood flow through the device depends on an adequately filled ventricle and a positive differential pressure between the inlet and the outlet of the VAD pump.
- this device Since this device produces flow continually and actively fills, it has the potential to create low pressure at the inflow in order to produce flow. “Excess Suction” occurs when the pressure in the inflow cannula decreases significantly—the pump begins to “suck” the ventricle closed, which would greatly reduce the pumping capability of the native heart and VAD. Decreasing the VAD's speed during an excess suction condition would allow the ventricle to refill, and normal blood flow to resume. Additionally, the detection of ventricular collapse and the ability to automatically adjust the pump's speed may aid in maintaining correct blood flow to the patient.
- Excess suction may be caused by occlusion of the tip of the inflow cannula or by completely emptying the ventricle (ventricular collapse).
- sustained excess suction typically triggers a diagnostic alarm on the pump controller.
- Information in addition to a simple binary indicator is desirable as it would allow a physician or technician to make a more precise diagnosis.
- the present invention addresses shortcomings associated with the prior art.
- an implantable pump system includes an implantable pump including a motor having a rotor and a stator.
- the stator includes a plurality of stator windings, and a motor controller is coupled to the motor to energize the windings so as cause the rotor to turn.
- a time-based system parameter of the pump is sampled and the system parameter is analyzed to calculate a suction probability index that provides an indication of the imminence of ventricle collapse.
- the pump system includes a processor that is programmed to analyze the parameter and calculate the suction probability index.
- the system parameter may include, for example, the pump current, power, speed, etc.
- the pump system may include an implantable flow sensing device, wherein the pump flow rate may be sampled and analyzed.
- various frequency domain and time domain techniques are disclosed for analyzing the system parameters to calculate the suction probability index.
- FIG. 1 schematically illustrates various components of an implantable pump system in accordance with embodiments of the present invention
- FIG. 2 is a cross-section view of an exemplary implantable pump in accordance with embodiments of the present invention.
- FIG. 3 is a block diagram illustrating aspects of a controller module in accordance with embodiments of the present invention.
- FIGS. 4–9 are block diagrams conceptually illustrating methods of detecting ventricle collapse in accordance with embodiments of the present invention.
- FIG. 1 illustrates a ventricle assist device (VAD) system 10 such as disclosed in U.S. Pat. No. 6,183,412, which is commonly assigned and incorporated herein by reference in its entirety.
- the VAD system 10 includes components designed for implantation within a human body and components external to the body.
- Implantable components include a rotary pump 12 and a flow sensor 14 .
- the external components include a portable controller module 16 , a clinical data acquisition system (CDAS) 18 , and a patient home support system (PHSS) 20 .
- the implanted components are connected to the controller module 16 via a percutaneous cable 22 .
- CDAS clinical data acquisition system
- PHSS patient home support system
- the VAD System 10 may incorporate an implantable continuous-flow blood pump, such as the various embodiments of axial flow pumps disclosed in U.S. Pat. No. 5,527,159 or in U.S. Pat. No. 5,947,892, both of which are incorporated herein by reference in their entirety.
- An example of a blood pump suitable for use in an embodiment of the invention is illustrated in FIG. 2 .
- the exemplary pump 12 includes a pump housing 32 , a diffuser 34 , a flow straightener 36 , and a brushless DC motor 38 , which includes a stator 40 and a rotor 42 .
- the housing 32 includes a flow tube 44 having a blood flow path 46 therethrough, a blood inlet 48 , and a blood outlet 50 .
- the stator 40 is attached to the pump housing 32 , is preferably located outside the flow tube 44 , and has a stator field winding 52 for producing a stator magnetic field.
- the stator 40 includes three stator windings and may be three phase “Y” or “Delta” wound.
- the rotor 42 is located within the flow tube 44 for rotation in response to the stator magnetic field, and includes an inducer 58 and an impeller 60 . Excitation current is applied to the stator windings 52 to generate a rotating magnetic field.
- a plurality of magnets 62 are coupled to the rotor 42 . The magnets 62 , and thus the rotor 42 , follow the rotating magnetic field to produce rotary motion.
- FIG. 3 conceptually illustrates aspects of the pump system 10 . More specifically, portions of the controller module 16 and the pump 12 are shown.
- the controller module 16 includes a processor, such as a microcontroller 80 , which in one embodiment of the invention is a model PIC16C77 microcontroller manufactured by Microchip Technology.
- the microcontroller 80 includes a multiple channel analog to digital (A/D) converter, which receives indications of motor parameters from the motor controller 84 .
- A/D analog to digital
- the controller module 16 may monitor parameters such as instantaneous motor current, motor voltage, and motor speed.
- the embodiment shown in FIG. 3 further includes an integral flow meter 124 .
- At least one flow sensor 14 is implanted down stream of the pump 12 .
- a flow sensor 14 may be integrated with the pump 12 .
- the flow meter 124 is coupled between the implanted flow sensor 14 and the microcontroller 80 .
- the flow meter 124 receives data from the flow sensor 14 and outputs flow rate data to the microcontroller 80 , allowing the system to monitor instantaneous flow rate.
- flow rate a true measure of system performance (flow rate) is available for analysis, in addition to pump parameters such as motor speed and current (power). Further, since the flow meter 124 is an integral component of the controller module 16 , flow rate may be displayed on the controller module display and flow rate data may be saved in the controller module memory.
- the motor controller 84 comprises a MicroLinear ML4425 Motor Controller from Fairchild Semiconductor.
- the operation of the brushless DC motor 38 of the present invention requires that current be applied in a proper sequence to the stator windings 52 to create the rotating field. Two stator windings 52 have current applied to them at any one time, and by sequencing the current on and off to the respective stator windings 52 , the rotating magnetic field is produced.
- the motor controller 84 senses back electromotive force (EMF) voltage from the motor windings 52 to determine the proper commutation phase sequence using phase lock loop (PLL) techniques.
- EMF back electromotive force
- a conductor such as a stator winding 52
- a voltage is induced.
- the voltage will increase with rotor speed 42 . It is possible to sense this voltage in one of the three stator windings 52 because only two of the motor's windings 52 are activated at any one time, to determine the rotor 42 position.
- An alternative method of detecting the rotor 42 position relative to the stator 40 for providing the proper stator winding 52 excitation current sequence is to use a position sensor, 5 such as a Hall effect sensor.
- a position sensor such as a Hall effect sensor.
- adding additional components, such as Hall effect sensors requires additional space, which is limited in any implanted device application.
- using a position detection device adds sources of system failures.
- the motor controller 84 operates to maintain the pump 12 at an essentially constant speed regardless of the differential pressure across the pump or the flow through the pump. As noted above, the motor controller 84 uses a PLL to control the speed of the pump motor 38 (commutation control). An additional analog closed-loop control circuit controls the onboard pulse width modulator (PWM) to maintain a desired speed setting. Both control-loops work in unison to maintain proper speed control.
- PWM pulse width modulator
- the motor controller 84 forms a PLL with a voltage-controlled oscillator (VCO), back-EMF sampling error amplifier, loop-filter, sequencer, and output driver.
- VCO voltage-controlled oscillator
- the motor controller 84 samples the instantaneous motor phase that is not energized to determine whether to increase or decrease the commutator (VCO) frequency.
- the VCO generates an output frequency (commutation rate) proportional to input voltage.
- a late commutation causes the error amplifier to charge the loop filter, increasing the VCO input while early commutation causes the error amplifier to discharge the loop filter, decreasing the VCO input.
- the PWM loop operating at approximately 25 kHz in exemplary embodiments, effectively maintains the desired speed setting once the PLL has reached steady-state (the desired target speed). Constant speed control of the three-phase pump motor, under varying or pulsatile load conditions, is achieved by varying the amount of current delivered to the stator windings proportionally to the motor's load.
- the commutation and PWM loops have, because of their associated filter networks, individual frequency and time domain responses associated with them.
- the frequency range over which the loop system will follow changes in the input frequency is called the lock-in range.
- the frequency range in which the loop acquires phase-lock is the capture range.
- the dynamic characteristics of the phase-locked loop, and thus the way the pump motor responds to changes in load, are controlled primarily by the loop filter.
- the filter network included in the PLL serves two major functions. First, it removes any noise and high-frequency components from the error amplifer's output providing an average (dc) voltage to be fed to the VCO's input, and it is the primary element that determines the dynamic performance of the loop including capture (pull-in) range, lock-in range, bandwidth, and transient response.
- the filter limits the speed of the loop to track changes in the input frequency (motor speed).
- the loop filter provides a “fly-wheel” effect, ensuring a rapid recapture of the signal if the system is thrown out of lock by a noise transient.
- Variations in differential pressure across the pump 12 will impart instantaneous changes in the speed of the pump motor 38 .
- the motor controller 84 will sense this change in speed through its back-EMF sampler and attempt to speed up or slow down the pump motor 38 , such that the preset speed is maintained.
- This instantaneous load change and corresponding correction performed by the motor controller will result in a corresponding variation in the pump's current waveform, speed waveform, and flow waveform.
- An instantaneous increase in the pump's load will cause an instantaneous decrease in pump speed and thus an instantaneous increase in pump current and decrease in flow rate.
- an instantaneous decrease in the pump's load will cause an instantaneous increase in pump speed and thus an instantaneous decrease in pump current and increase in flow rate.
- the pump's current (and therefore power), speed, and flow waveforms correlate well with changes in the pump's load.
- These waveforms may be used to calculate the patient's heart rate, instantaneous and mean blood flow rate, regurgitant flow, instantaneous and mean power consumption, the pump's efficiency, etc.
- These waveforms also indicate when the pump's speed is set too high and the ventricle begins to collapse. This condition exists when the flow and/or current waveforms are highly-asymmetric and/or their peaks appear to contain multiple ripples or are flattened (clipped). Additionally, waveforms with short negative rise-times (attack) followed by slower positive exponential fall-times (decay) indicate suction.
- the aforementioned signals, current, speed, and flow are time-continuous band-limited signals.
- the current signal is a composite signal containing the motor controller's PWM frequency, the patients heart rate (assuming the heart is beating), and other frequencies relating to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic resistance, etc.).
- the pulse-width modulation frequency typically is approximately 25 kHz and the patient's heart rate is approximately 0.7 Hz to 4.0 Hz.
- the power signal is the product of the pump motor current and pump motor voltage (a constant scalar) and is therefore a composite signal which, like the current, contains the motor controller's pulse-width modulation (PWM) frequency, the patients heart rate (assuming there is a heart rate), and other frequencies relating to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic resistance, etc.).
- PWM pulse-width modulation
- the pulse-width modulation frequency is approximately 25 kHz and the patient's heart rate is approximately 0.7 Hz to 4.0 Hz.
- the speed signal typically contains the heart rate of the patient (assuming the heart is beating) as the dominant frequency along with other frequencies related to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic pressure, etc.).
- the angular momentum of the rotor impeller and viscosity of the blood dampen abrupt changes in speed and thus the bandwidth of this signal is typically under 30 Hz.
- the flow signal typically contains the heart rate of the patient (assuming the heart is beating) as the dominant frequency along with other frequencies related to certain physiologic responses within the patient's cardiovascular system (e.g. valve openings and closures, changes in systemic pressure, etc.).
- Embodiments of the present invention employ various mechanisms to detect the onset and/or presence of ventricular collapse based on the processing and/or analysis of certain inherent pump system parameters (e.g. flow, current, speed, etc.). These analysis techniques are performed in the time domain and frequency domain.
- Time domain mechanisms include correlation techniques as well as linear and non-linear signal processing.
- Frequency domain mechanisms include various real-time spectral analysis methods using Fourier Transforms such as the Fast Fourier Transform (“FFT”) and the Discrete Fourier Transform (“DFT”), as well as other linear and non-linear signal processing techniques.
- FFT Fast Fourier Transform
- DFT Discrete Fourier Transform
- a physiologically appropriate flow(t) waveform is assumed to be quasi-sinusoidal at a single frequency proportional to the patient's native heart rate (i.e. fundamental frequency).
- the corresponding physiologically appropriate flow(f) waveform will be a single narrow spectral peak at the same single frequency proportional to the patient's native heart rate.
- the flow(f) waveform will contain additional spectral peaks corresponding to flow contributions at varying frequencies.
- the Fourier Series may be used to compute the fundamental and harmonic components from time domain signals that are continuous and periodic. Many invivo waveforms that may denote suction, however, are not periodic, and further, the frequency components of such waveforms may not be harmonically related to the fundamental frequency. In accordance with aspects of the present invention, many frequency components, both harmonically related and not, about the fundamental are analyzed to precisely detect suction.
- FIG. 4 illustrates ventricular collapse methods based on a spectral analysis in accordance with embodiments of the present invention.
- the embodiments shown in block diagram form in FIG. 4 operate on the principle that the onset of ventricular collapse is imminent when the flow and/or current waveforms are asymmetric and/or their peaks appear to contain multiple ripples or are flattened (clipped). Variations in the flow, speed, current, and power waveforms in the time-domain will result in corresponding variation in their frequency-domain representations.
- one or more time-continuous band-limited signals are received and converted to a digital signal.
- the flow signal provided via the flow sensor 14 and flow meter 124 is specifically analyzed for suction detection, though one or more of the current, power, speed, etc. signals available may be used.
- the spectral content of the sampled signals are computed in block 212 .
- a Fourier Transform such as the Discrete Fourier Transform (“DFT”), and/or Fast Fourier Transform (“FFT”) may be used to obtain the frequency-domain responses for the signals converted in block 210 .
- DFT Discrete Fourier Transform
- FFT Fast Fourier Transform
- the FFT is more efficient computationally than is the DFT and is more easily realized in hardware and/or software. Continuous conversion of the time-continuous signals from the time-domain to the frequency-domain provides real time spectral content information about these signals.
- the array generated in block 212 is processed by spectral analysis equations in block 214 to generate a suction probability index in block 216 , which may be expressed as a percentage.
- the suction probability index provides an indication of the imminence of ventricle collapse in block 218 .
- Known methods to detect the onset or presence of ventricular collapse use a binary “suction detect” indicator when onset is discovered. No “suction indices” are used. The use of “suction indices” leads to a more precise diagnosis and gives the physician access to more information than a simple binary answer.
- exemplary spectral analysis equations 214 used in various embodiments of the invention for processing the data to generate the suction probability index 216 include analyses based on harmonic distortion, total spectral distortion (harmonic distortion and noise), sub-fundamental distortion (distortion below the fundamental frequency), super-fundamental distortion (distortion above the fundamental frequency), the ratio of the super-fundamental distortion to the sub-fundamental distortion, super-physiologic distortion (distortion at frequencies above the assumed maximum physiologic fundamental frequency—typically 4 Hz or 240 BPM), and the spectral dispersion or “width” of the resulting flow(f) waveform.
- harmonic distortion harmonic distortion and noise
- sub-fundamental distortion disortion below the fundamental frequency
- super-fundamental distortion disortion above the fundamental frequency
- super-physiologic distortion dispersion or “width” of the resulting flow(f) waveform.
- the spectral distortion factor measures the ratio of all energy contributed by all frequencies about the fundamental frequency with respect to the fundamental frequency. A higher distortion ratio indicates a higher probability of suction.
- n indicates the spectral component's index/position in the resulting array
- x is the last index/position in this array
- dF represents the frequency resolution/interval of the resulting FFT operation in Hertz
- f 1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array.
- the harmonic distortion factor measures the ratio of energy contributed by all harmonics about the fundamental frequency with respect to the fundamental frequency.
- n indicates the n th harmonic in the resulting array
- x is the highest harmonic in this array
- f 1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array
- the sub-fundamental distortion factor measures the additive frequency contributions below the fundamental frequency with respect to the fundamental frequency.
- n 1 n ⁇ ( f1 ) - 1 ⁇ ⁇ [ A ⁇ [ f ( n ⁇ dF ) ] ] 2 ] ⁇ 100 ⁇ A ⁇ [ f 1 ] ⁇
- n indicates the spectral component's index/position in the resulting array
- dF represents the frequency resolution/interval of the resulting FFT operation in Hertz
- f 1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array
- n(f1) is the index/position of the fundamental.
- the super-fundamental distortion factor measures the additive frequency contributions above the fundamental frequency with respect to the fundamental frequency.
- n n ⁇ ( f1 ) + 1 x ⁇ ⁇ [ A ⁇ [ f ( n ⁇ dF ) ] ] 2 ] ⁇ 100 ⁇ A ⁇ [ f 1 ] ⁇
- n indicates the spectral component's index/position in the resulting array
- x is the last index/position in this array
- dF represents the frequency resolution/interval of the resulting FFT operation in Hertz
- f 1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array
- n(f1) is the index/position of the fundamental.
- the super/sub fundamental distortion factor measures the ratio of additive frequency contributions above the fundamental frequency to the additive frequency contributions below the fundamental frequency.
- the spread of the waveform is measured.
- a physiologically appropriate waveform in the time domain is quasi-sinusoidal at a single frequency proportional to the patient's native heart rate, and hence, the corresponding physiologically appropriate waveform in the frequency domain will be a singly narrow spectral peak at the same single frequency proportional to the patient's native heart rate. Deviations from this quasi-sinusoidal case may indicate suction as well as other defects.
- the flow(f) waveform will contain additional flow contributions at varying frequencies and will thus begin to “widen”.
- the probability that suction is imminent or present increases proportionally to the width of flow(f).
- the measure of the width of flow(f) about the fundamental frequency is the square-root of the mean-squared variation about the fundamental frequency.
- the spectral dispersion factor measures the “width” of the flow(f), current(f), speed(f), and/or power(f) signals:
- FIGS. 5 and 6 Some alternatives to applying the spectral content of the measured signal to spectral analysis equations are shown in FIGS. 5 and 6 , where the real time spectral content measured signal is compared to a predetermined spectral mask.
- the spectral content 220 generated by the FFT 212 is compared to a predetermined spectral mask 222 in a combiner block 224 .
- the presence of suction is determined based on the comparison.
- the signals whose spectral components fall within the mask indicate suction and, conversely, signals whose spectral components fall outside the mask indicate normal flow.
- the time domain responses are converted to frequency domain through the application of a synchronous switched-capacitor filter 230 .
- the frequency response of the filter 230 is controlled by a clock source one hundred times the desired pass-band frequency.
- a phase-locked loop 232 generates this clocking signal to the filter 230 by receiving the output from a zero crossing detector 234 and multiplying the incoming fundamental frequency by an integer multiplier 236 , the value of which is selected by a digital input element such as a microcontroller. Incrementing the integer multiplier will cause the synchronous filter to “track” the incoming signal and output the spectral amplitude of the fundamental frequency, first harmonic, second harmonic, etc. The sum of the individual spectral amplitudes results in a frequency-domain representation of the time-domain signals.
- a comparison may then be made between the real-time spectral content 220 of these signals and the predetermined spectral mask 222 .
- Signals whose spectral components fall within the mask indicate suction and, conversely, signals whose spectral components fall outside the mask indicate normal flow.
- FIG. 7 illustrates a method that cross-correlates the incoming time-sampled signal (for example, the flow or current signal) with predetermined time-domain waveforms 250 exemplifying the imminence of ventricular collapse.
- the waveforms 250 are selected in block 252 sequentially or based on the probability of occurrence in that particular patient derived experientially through clinical evaluation.
- a correlation coefficient is generated in block 254 , where
- 1 signifies a perfect “match” and
- 0 indicates no correlation at all.
- the correlation coefficient is compared to predetermined thresholds in block 256 to derive a suction probability index. If the calculated correlation coefficient exceeds a predetermined value, ventricular collapse is imminent. Conversely, if the calculated correlation coefficient is below the predetermined value, suction is not present.
- the incoming time-sampled signal may be cross-correlated with time-domain representations of sine waves at integer multiples of the incoming fundamental frequency.
- the sum of the individual spectral amplitudes results in a frequency-domain representation of the time-domain signals.
- a comparison is then made between the real-time spectral content of these signals and a predetermined spectral mask as in the embodiments shown in FIGS. 5 and 6 . Signals whose spectral components fall within the mask indicate suction and, conversely, signals whose spectral components fall outside the mask indicate normal flow.
- Still further analysis methods continuously time-sample signals representing system parameters such as flow, speed, current, or power, and calculate the slope between a series of data points. By comparing the calculated slope to a predetermined value, ventricular collapse may be detected. This may also be applied to the first or second derivatives of the flow, current, speed, and/or power signals.
- the derivative of the time-sampled signal, such as flow, with respect to time is calculated in block 260 , which yields blood acceleration. Therefore, a large negative dflow(t)/dt indicates the presence of ventricular collapse.
- the calculated derivative is provided as one input to a comparitor 262 .
- An adjustable suction detect threshold value 264 is provided as the second input to the comparitor 262 such that the derivative calculated in block 260 is compared to a predetermined value. Based on the output of the comparitor 262 , the presence of collapse is determined in block 266 .
- the second derivative of the measured parameter (e.g. d 2 flow(t)/dt 2 , d 2 current(t)/dt 2 , d 2 power(t)/dt 2 , or d 2 speed(t)/dt 2 ) is calculated in block 261 and compared to a predetermined value to detect suction based on changes in the aforementioned signals.
- the aforementioned methods for detecting the imminence of ventricular collapse are implemented in software, hardware, or both.
- Software implementations include using the microcontroller 80 used provided in the controller module 16 .
- a stand-alone microcontroller or a digital signal processor (“DSP”) may be used.
- Exemplary hardware implementations may include a field programmable gate array (“FPGA”), a complex programmable logic device (“CPLD”), application specific integrated circuits (“ASIC”), discrete analog and/or digital components, etc.
Abstract
Description
wherein n indicates the spectral component's index/position in the resulting array; x is the last index/position in this array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; and f1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array. Since the spectral analysis of the flow rate signal pertains to the AC component, and not the offset, the range of interest does not include n=0 because the mean flow rate or DC component of the flow(f) waveform occurs at n=0. This is true for all of the frequency domain suction probability indices contained herein.
wherein n indicates the nth harmonic in the resulting array; x is the highest harmonic in this array; f1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and fn represents integer multiples of the fundamental f1 from n=2 (second harmonic) to x (xth harmonic).
wherein n indicates the spectral component's index/position in the resulting array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; f1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and n(f1) is the index/position of the fundamental.
wherein n indicates the spectral component's index/position in the resulting array; x is the last index/position in this array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; f1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; and n(f1) is the index/position of the fundamental.
wherein n indicates the spectral component's index/position in the resulting array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; x is the last index/position in this array; and n(f1) is the index/position of the fundamental.
wherein fh is a spectral peak at frequency=4 Hz; n indicates the spectral component's index/position in the resulting array; x is the last index/position in this array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; f1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array.
wherein f1 is the fundamental frequency, the maximum (amplitude) spectral peak in the FFT resultant array; dF represents the frequency resolution/interval of the resulting FFT operation in Hertz; n indicates the spectral component's index/position in the resulting array; and N is the last index/position in this array. Since the analysis of spread flow is concerned with the wave shape, and not the offset, the range of interest does not include n=0 because the mean flow rate or DC component of the flow(f) waveform occurs at n=0.
Claims (34)
Priority Applications (1)
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US10/501,275 US7175588B2 (en) | 2002-01-08 | 2003-01-08 | Method and system for detecting ventricular collapse |
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US34655502P | 2002-01-08 | 2002-01-08 | |
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US10/501,275 US7175588B2 (en) | 2002-01-08 | 2003-01-08 | Method and system for detecting ventricular collapse |
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EP (1) | EP1469770B1 (en) |
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DE60334677D1 (en) | 2010-12-09 |
EP1469770A4 (en) | 2007-06-27 |
AU2003202250A8 (en) | 2003-07-24 |
WO2003057013A3 (en) | 2003-11-06 |
CN1638824A (en) | 2005-07-13 |
JP2005514094A (en) | 2005-05-19 |
EP1469770B1 (en) | 2010-10-27 |
ATE485850T1 (en) | 2010-11-15 |
US20050004418A1 (en) | 2005-01-06 |
AU2003202250A1 (en) | 2003-07-24 |
EP1469770A2 (en) | 2004-10-27 |
CA2471484A1 (en) | 2003-07-17 |
WO2003057013A2 (en) | 2003-07-17 |
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